Job Title : Data Scientist AWS Bedrock Location : Chicago, IL About the Role
We are seeking a highly skilled Data Scientist with hands-on experience in AWS Bedrock to design, build, and scale generative AI and machine learning solutions. The ideal candidate has a strong foundation in Python, applied ML, LLMs, and cloud-native development with a focus on production-grade models and prompt engineering.
Key Responsibilities
- Develop, fine-tune, and deploy generative AI / LLM solutions using AWS Bedrock , including foundation models such as Claude, Llama, and Titan.
- Build end-to-end ML workflows leveraging AWS services (S3, Lambda, SageMaker, Step Functions, API Gateway, DynamoDB, RDS, etc.).
- Design and implement prompt engineering strategies, evaluation frameworks, and model optimization techniques.
- Integrate Bedrock-powered AI capabilities into applications via APIs and SDKs.
- Collaborate with cross-functional teams to identify business problems and translate them into scalable AI / ML solutions.
- Perform data preprocessing, feature engineering, statistical modeling, and experimentation.
- Develop scalable pipelines for model training, inference, and monitoring.
- Conduct A / B testing, model performance evaluations, and continuous improvement activities.
- Ensure adherence to security, compliance, and responsible AI best practices within AWS.
- Produce clear technical documentation, reports, and model explainability outputs.
Required Skills & Qualifications
Bachelor's or Master's in Computer Science, Data Science, Engineering, Mathematics, or related field.3 7 years of experience as a Data Scientist or ML Engineer.Strong hands-on expertise with AWS Bedrock , including provisioning, model selection, and orchestration.Advanced proficiency in Python , including libraries such as NumPy, pandas, scikit-learn, PyTorch or TensorFlow.Experience building and deploying ML / LLM applications in AWS.Knowledge of vector databases (e.g., Pinecone, FAISS, OpenSearch) and RAG pipelines.Strong grasp of data modeling, statistics, NLP, and machine learning algorithms.Familiarity with CI / CD, MLOps, containerization (Docker), and version control (Git).Strong problem-solving abilities, analytical mindset, and communication skills.Preferred Qualifications
Experience fine-tuning LLMs using SageMaker or custom training pipelines.Prior work with multimodal models, retrieval-augmented generation (RAG), or agent-based architectures.Certification : AWS Solutions Architect , AWS Machine Learning Specialty , or equivalent.Experience integrating Bedrock with real-time applications and microservices.